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ORIGINAL ARTICLE
Year : 2019  |  Volume : 32  |  Issue : 1  |  Page : 101-105

Role of elastography in characterization of solid breast masses


1 Department of Radiology, Faculty of Medicine, Menoufia University, Shebeen El-Kom, Egypt
2 Department of Radiology, National Liver Institute, Menoufia University, Shebeen El-Kom, Egypt
3 Department of Radiology, Birket Asabaa Hospital, Berket El-Sabae, Menoufia, Egypt

Date of Submission04-Jun-2017
Date of Acceptance21-Jul-2017
Date of Web Publication17-Apr-2019

Correspondence Address:
Hanan M Khallaf
11 Elnozha Street, Berket El-Sabae, Menoufia 32511
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_405_17

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  Abstract 


Objectives
The aim of this study was to study the diagnostic performance of elastography in characterization of solid breast masses.
Background
Elastography is an imaging modality that can calculate the elasticity of tissues, based on the well-established principle that benign lesions are soft and malignant lesions are hard. It is an easy procedure with high diagnostic performance, which can be easily integrated with the B-mode ultrasound examination in the same session to improve its specificity.
Patients and methods
A total of 30 female patients were included in this prospective study in the period from February 2016 to February 2017 with a complaint of breast mass. We examined the patients using ultrasonography and strain elastography. Then, we compared the findings of ultrasonography and elastography with pathology findings to assess their diagnostic performance.
Results
Among the 30 breast masses, 14 were benign and 16 were malignant. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ultrasonography were 100, 43, 67, and 100%, respectively. Qualitative elastography (Tsukuba score) had a sensitivity of 69%, specificity of 86%, PPV of 85%, and NPV of 71%. Quantitative elastography, assessed using the strain ratio, was a good discriminant for malignancy (area under the receiver operating curve = 0.94, P = 0.001). Our results revealed a cutoff point for malignancy of more than2.7; by using this threshold, the diagnostic performance of the strain ratio was 94% sensitivity, 86% specificity, 88% PPV, and 92%NPV.
Conclusion
Elastography has great diagnostic performance in distinguishing between benign and malignant breast masses.

Keywords: benign, breast, elastography, malignant


How to cite this article:
Maaly MA, Abdel Lattif HA, Elsakhawy MM, Khallaf HM. Role of elastography in characterization of solid breast masses. Menoufia Med J 2019;32:101-5

How to cite this URL:
Maaly MA, Abdel Lattif HA, Elsakhawy MM, Khallaf HM. Role of elastography in characterization of solid breast masses. Menoufia Med J [serial online] 2019 [cited 2019 Aug 25];32:101-5. Available from: http://www.mmj.eg.net/text.asp?2019/32/1/101/256110




  Introduction Top


Around the world, breast malignancy is the most widely recognized type of malignancy and the most common cause of cancer-related death among females. It accounts for 29% of the novel cases of cancer and 15% of cancer-related death and is the second cause of cancer-specific death [1].

Conventional ultrasonography is an important adjunct to mammography and other breast imaging modalities; it affords high sensitivity in evaluation of breast masses and in distinguishing benign solid breast lesions from malignant solid breast lesions [2]. However, ultrasonography is not flawless as it is subjective and has low specificity [3].

Principle of elastography is that after compression of a tissue, a strain (movement) is formed within the tissue and the strain is less in harder tissue than in softer tissue. Therefore, by measuring the strain induced in the tissue by compression, we can calculate tissue stiffness, which may help in establishing a breast malignancy diagnosis [4].

Evaluating breast elasticity can be achieved by numerous imaging methods. These methods all have a high diagnostic performance in distinguishing between benign and malignant breast lesions [5].

The mainstay in the diagnosis of doubtful breast lesions remains breast biopsy, but the pathological result is benign in up to 75% of all cases. Therefore, we can decrease the number of unnecessary biopsies by depending on elastography, which is a reliable, noninvasive, and economical method in distinguishing benign from malignant breast lesions [6].

In this study, we assessed the diagnostic importance of ultrasound (US) elastography in distinguishing benign from malignant breast masses.


  Patients and Methods Top


After approval of the Local Institutional Ethical Committee of Menoufia University Hospital and obtaining written consents from all patients to participate in our study, this study was done in the female section of the imaging unit/radiology department of the Tanta Cancer Institute. Patients were referred from the outpatient clinic of the internal medicine and surgery units from February 2016 to February 2017. The study was prospectively carried out on 30 female patients with breast lesions.

Inclusion criteria included patients who have breast masses and positive US findings.

Exclusion criteria included cases with breast implants and cases with superficial (<5 mm deep to the skin surface) and cutaneous lesions.

All of the patients underwent the following procedures: clinical examination, including full history taking and physical examination, and then all patients had a conventional B-mode US examination and real-time elastography. Samples were taken from the masses with fine-needle aspiration cytology, core biopsy, surgical excision, or radical surgery.

The study was performed using US device (Aplio–500; Toshiba Medical Systems Corporation, Otawara, Japan) equipped with real-time elastography software and a 5–10 MHz linear array electronic probe.

First, breast lesions were evaluated by conventional B-mode US, and images were assigned to one of the five categories of the BIRADS criteria for US [7].

On the same session, real-time free-hand elastography investigation was performed and evaluated using both qualitative and quantitative techniques.

In the qualitative assessment of the elastography images, we categorized each breast mass according to the fiver-point Tsukuba scoring classification [Figure 1] [4].
Figure 1: The Tsukuba scoring system. (a) ES 1: The entire lesion is coded in green, indicating a soft mass. (b) ES 2: mass coded in blue and green mosaic, indicating that the internal structure is heterogeneously soft-hard. (c). ES3: mass is coded in blue in the middle surrounded by green; this indicates that the outer structure is soft whereas the center is hard (d) ES4: the entire mass is blue, indicating that it is entirely hard and has a firm internal structure. (e) ES5: the mass and surrounding tissue is coded in blue covering an area larger than the size of the mass.

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Quantitative assessment of the elastography images was done using strain ratio.

Data were collected, formulated, and statistically analyzed using SPSS, version 20 (SPSS Inc, Chicago, Illinois, USA). The following statistics were applied: descriptive statistics, in which quantitative data were presented in the form of mean, SD, and range and qualitative data were presented in the form of numbers and percentages, and analytical statistics used to find out the possible association between studied factors and the targeted disease. Receiver operating characteristic curve analysis was used to determine the optimal threshold, area under the curve (AUC), specificity, and sensitivity of the tested parameters. The level of significance was set at a P value of 0.05.


  Results Top


The study was prospectively carried on 30 female patients with breast lesions. There were 14 patients with benign breast lesions and 16 patients with malignant breast lesions.

The mean age of the patients with benign breast lesion was 37.8 ± 12.6 years, and the mean age of patients with malignant breast lesion was 51.9 ± 11.1 years.

The histopathological results of breast lesions in the study are shown in [Table 1].
Table 1: Histopathological diagnosis of breast lesions

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After US examination, one (3.3%) patient had BIRADS category II, five (16.7%) patients had BIRADS category III, 13 (43.3%) patients had BIRADS category IV, nine (30%) patients had BIRADS category V, and two (6.7%) patients had BIRADS category VI.

The sensitivity of US was 100%, specificity was 43%, and accuracy was 73%. The positive predictive value (PPV) and negative predictive value (NPV) were 67 and 100%, respectively [Table 2].
Table 2: Diagnostic performance of the BIRADS, elasticity score, and strain ratio in predicting malignant lesion

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After elastographic examination, three (10%) patients had elasticity score of 1, nine (30%) patients had elasticity score of 2, five (16.7%) patients had elasticity score of 3, four (13.3) patients had elasticity score of 4, and nine (30%) patients had elasticity score of 5.

The sensitivity of the elasticity score was 69%, specificity was 86%, PPV was 85%, NPV was 71%, and accuracy was 71% [Table 2].

Regarding strain ratio, there was highly significant difference between the mean strain ratio in the patients with benign lesions (1.73 ± 1.15) and the mean strain ratio in the patients with malignant lesions (5.62 ± 2.62) [Figure 2], [Figure 3], [Figure 4].
Figure 2: A 30-year-old female patient. (a) Gray-scale ultrasound revealed a 17 × 8 mm, well-circumscribed, homogeneous mass in the right breast at 3, BIRADS 3. (b) The strain ratio on elastography is measured as 0.56 with an elasticity score of 1. This mass was considered as benign owing to sonoelastography features and was diagnosed as fibroadenoma on histopathologic evaluation.

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Figure 3: A 52-year-old female patient. (a) Gray-scale ultrasound showing a 37 × 26 mm, irregular bordered, speculated, heterogeneous lesion evaluated as BIRADS 5 in the right breast at 9. (b) Elastogram strain ratio was measured as 3.6 with an elasticity score of 5. This mas was evaluated as malignant by its sonoelastography features and was diagnosed as infiltrating ductal carcinoma after histopathological examination.

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Figure 4: A 56-year-old female patient (a) Gray-scale ultrasound showing a 22 × 18 mm, speculated heterogonous mass with small satellite nearby evaluated as BIRADS 5 in the left breast at 2 o'clock position with interstitial edema and thick skin. (b) Elastogram strain ratio was measured as 7.5 with an elasticity score of 5. This mas was evaluated as malignant by its sonoelastography features and was diagnosed as Scirrhous type of invasive ductal carcinoma after histopathological examination.

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Receiver operating curve analysis of the strain ratio [Figure 5] revealed that the best cutoff point was 2.7, with a sensitivity of 94%, specificity of 86%, PPV of 88%, NPV of 92%, and accuracy of 90% [Table 2].
Figure 5: Diagnostic performance of strain ratio (ROC curve). ROC, receiver operating characteristic.

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  Discussion Top


Elastography is a noninvasive imaging technique that calculates the elasticity of tissues. Usually, normal breast tissue is softer than cancer breast tissue. Using elastography, we can assess the elasticity of breast using color-coded superimposition on the B-mode image and then we can distinguish benign from malignant breast masses [8].

In our study, we included 30 patients. All lesions were subjected to two-dimensional US studies, which was followed by elastographic evaluation, and scored according to Tsukuba score into one of the five elastoscoring categories. Then, strain ratio was calculated for each lesion and compared with the histological results after radical surgery, excisional, true-cut biopsy, or fine-needle aspiration cytology.

The mean age for all patients was 45.3 years (age range: 20–70 years). Overall, 14 patients with benign lesions had a mean age of 37.8 years, and the remaining 16 patients with malignant lesions had a mean age of 51.9 years. It was found that the mean age for malignant lesions was higher than that for benign lesions, and this difference was statistically significant (P = 0.002).

This agrees with the study of Bojanic et al. [9] who found that the mean age for patients with benign lesions was 50 years and the mean age for those with malignant lesions was 63 years.

The final pathologic diagnoses in our study revealed 14 (46.7%) benign breast lesions, including eight (26.7%) fibroadenomas, two (6.7%) focal adenosis, one (3.3%) granulomatous mastitis, one (3.3%) atypical fibroadenoma, one (3.3%) hamartoma, and one (3.3%) intraductal papilloma.

The remaining 16 (53.3%) lesions were diagnosed pathologically as malignant lesions; they included four (13.3%) infiltrating ductal carcinomas, six (20%) ductal carcinomas in situ, two (6.7%) invasive lobular carcinoma, three (10%) medullary carcinoma, and one (3.3%) schirrous carcinoma.

According to the results, the sensitivity of conventional US was 100%, specificity was 43%, and accuracy was 73%. The PPV and NPV were 67 and 100%, respectively.

These results agree with the study done by Balcik et al. [10], in which after examination of 135 mass lesions in 132 female patients, they found that the sensitivity of conventional US was 98.5%, specificity was 56.2%, and accuracy was 77.7%. The PPV and NPV were 71.1 and 97.2%, respectively.

Moreover, similar results were found in the study done by Arslan et al. [11] in which they examined 81 breast lesions and found that the sensitivity of conventional US was 100%, specificity was 11.6%, and accuracy was 53%. The PPV and NPV were 50 and 100%, respectively.

US is not flawless. Annual mammography and thorough breast clinical examination are crucial. One of the disadvantages of US is that it depends on the experience of the examiner; another one is that the quality of the machine can affect the findings. All these drawbacks can lead to false-positive and false-negative results [12].

According to Tsukuba scoring, lesions in our study were classified into five elastoscores, as previously described.

When considering an elasticity score cutoff point of 3, the sensitivity was 69%, specificity was 86%, PPV was 85%, NPV was 71%, and accuracy was 7%.

Similar results were found in the study done by Balcik et al. [10]. They found that the sensitivity of elasticity score was 80.0%, specificity was 90.8%, and accuracy was 85.2%. The PPV and NPV were 90.3, and 80.8%, respectively, when using cutoff point of elasticity score 3.

These results agree with the study done by Arslan et al. [11], who found that the sensitivity of elasticity score was 71.7%, specificity was 97.7%, and accuracy was 85.1%. The PPV and NPV were 96.4 and 79.2%, respectively, when using cutoff point of elasticity score 3.

In addition, the study done by Stoian et al. [13] showed similar results.; they considered elasticity score 1, 2, and 3 for benign and elasticity score 4 and 5 for malignant and found that the sensitivity of elasticity score was 82.4%, specificity was 81.9%, and accuracy was 82.2%. The PPV and NPV were 80.3 and 83.9%, respectively.

In our study, there was highly significant difference between the mean strain ratio among the patients with benign lesions (1.73 ± 1.15) and those with malignant lesions (5.62 ± 2.62).

This comes in agreement with the study of Balcik et al. [10] who found highly significant difference between the mean strain ratios among the patients with benign lesions (2.8 ± 1.7) and those with malignant lesions (8.4 ± 4.8).

In our study, the best cutoff value for strain ratio to differentiate between benign and malignant breast lesions was found to be at 2.7 (AUC = 0.94).

When using this cutoff point, the sensitivity was 94%, specificity was 86%, NPV was 92%, PPV was 88%, and accuracy was 90%.

These results agree with the study done by Arslan et al. [11], who set a cutoff value for strain ratio at 2.84 and found sensitivity of 78.9% and specificity of 90.7%. NPV was 82.9%, PPV was 88.2%, and accuracy was 85.1%. The AUC was 0.93.

This comes in agreement with the study of Balcik et al. [10], who found the best cutoff value of strain ratio at 4.52 and found sensitivity of 85.5% and specificity of 84.8%. NPV was 84.8%, PPV was 85.5%, and accuracy was 85.2%. The AUC was 0.92.

Our results agree with the study done by Zhi et al. [14], which was performed on 559 solid lesions. The strain ratios of benign lesions (mean: 1.83) and malignant lesions (mean: 8.38) were significantly different (P < 0.001). When a cutoff point of 3.05 was introduced, strain ratio method had 92.4% sensitivity, 91.1% specificity, and 91.4% accuracy. The AUC was 0.94.

Our study showed that US BIRADS showed the highest sensitivity in predicting malignant lesion with a sensitivity of 100% followed by strain ratio with a sensitivity of 94% and then the elasticity score with a sensitivity of 69%.

Moreover, the elasticity score and the strain ratio showed similar specificity (86%) followed by US BIRADS (69%).

Overall the accuracy in predicting the malignant lesion was highest for the strain ratio with 90% followed by the US BIRADS with 73%, and then the elasticity score with 71%.

Leong et al. [15] compared the performance of breast elastography and conventional US in distinguishing breast lesions in a prospective study involving 110 lesions. Sensitivity, specificity, and accuracy were 88.5, 42.9, and 53.6%, respectively, for conventional US, and 100, 73.8, and 80%, respectively, for elastography. The conclusion of the study was that elastography has higher sensitivity and accuracy than US.

When comparing between conventional US (BIRADS category) and elastography (Tsukuba scoring system), most studies have reported better specificity for elastography and higher sensitivity for conventional US, with the exception of the study done by Cho et al. [16], which reported same degrees of sensitivity (82%) and lowered specificity (84%) for elastography compared with conventional sonography (89%).


  Conclusion Top


Elastography is an easy and accessible procedure with high diagnostic performance that can be easily integrated with the B-mode US examination in the same session and improves its specificity.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

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